Resazurin to determine the minimum inhibitory concentration on antifungal susceptibility assays for Fonsecaea sp. using a modified EUCAST protocol.
Tatiana Sobianski HermanCamila da Silva GoerschAnamelia Lorenzetti BoccaLarissa FernandesPublished in: Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] (2024)
Chromoblastomycosis is a fungal chronic disease, which affects humans, especially in cutaneous and subcutaneous tissues. There is no standard treatment for Chromoblastomycosis, and it is a therapeutic challenge, due natural resistance of their causative agents, inadequate response of patients and common cases of relapse. Protocols for determination of antifungal drugs susceptibility are not standardized for chromoblastomycosis agents and endpoint definition is usually based on visual inspection, which depends on the analyst, making it sometimes inaccurate. We presented a colorimetric and quantitative methodology based on resazurin reduction to resofurin to determine the metabolic status of viable cells of Fonsecaea sp. Performing antifungal susceptibility assay by a modified EUCAST protocol allied to resazurin, we validated the method to identify the minimum inhibitory concentrations of itraconazole, fluconazole, amphotericin B, and terbinafine for eight Fonsecaea clinical isolates. According to our data, resazurin is a good indicator of metabolic status of viable cells, including those exposed to antifungal drugs. This work aimed to test resazurin as an indicator of the metabolic activity of Fonsecaea species in susceptibility assays to antifungal drugs. Species of this genus are the main causative agents of Chromoblastomycosis, which affects humans.
Keyphrases
- candida albicans
- induced apoptosis
- cell cycle arrest
- end stage renal disease
- high throughput
- randomized controlled trial
- chronic kidney disease
- newly diagnosed
- gold nanoparticles
- gene expression
- ejection fraction
- endoplasmic reticulum stress
- hydrogen peroxide
- peritoneal dialysis
- drug induced
- cell death
- big data
- oxidative stress
- cell proliferation
- living cells
- sensitive detection
- deep learning
- combination therapy
- smoking cessation
- solid phase extraction
- label free
- cell wall